Offering a New Approach to Optimal Scheduling of Tasks in the Cloud Using Chromosome Portioning

Journal Title: International Research Journal of Applied and Basic Sciences - Year 2014, Vol 8, Issue 11

Abstract

It is for a long time that the cloud computing shows off in the range IT. Scheduling of the Cloud services have influenced by providers cost benefit of the computing paradigm . In this Scenario the whole of tasks must be Scheuled in the best way so that the cost and runtime reduce. In this thesis we have tried to discuss scheduling tasks based on genetic algorithms and parallelism will be investigated in detail. In the proposed method, independent tasks on homogeneous cloud environment are considered. In this algorithm, each task in addition to runtime, has survival time (That is, each task has a limited time to run if not running in a particular period its implementation value is reduced) Just like real-time systems and the factors of survival time for each task show its priority task to run.The main advantage of the proposed model is that it is both reduceing the total execution time and trying to complete each task in the fastest possible time, before the deadline finishes. This issue is particularly important in real-time systems and compared to a simple real-time scheduling algorithm its execution time is less.Simulation of the algorithm in Cloudism environment shows that by increasing the resources for a fixed number of tasks, how much run time can be reduced to the system.

Authors and Affiliations

Ali Heydarzadegan*| Department of Computer Engineering,BeyzaBranch,Islamic Azad University,Beyza,Iran, email:A.heidarzadegan@yahoo.com, Yaser Nemati,Mohammad Iman Jamnezhad| Department of Computer Engineering,BeyzaBranch,Islamic Azad University,Beyza,Iran, Mohsen Moradi| Department of Computer Engineering,BeyzaBranch,Islamic Azad University,Beyza,Iran

Keywords

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  • EP ID EP6839
  • DOI -
  • Views 307
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How To Cite

Ali Heydarzadegan*, Mohammad Iman Jamnezhad, Mohsen Moradi (2014). Offering a New Approach to Optimal Scheduling of Tasks in the Cloud Using Chromosome Portioning. International Research Journal of Applied and Basic Sciences, 8(11), 2057-2061. https://europub.co.uk/articles/-A-6839